Your whole farm, parcel by parcel, on a single map.

Parcels can carry labels with the block (tarla), parcel number, cadastral number, area or owners — from the data you upload — in the colour and size you choose. Layers switch on and off independently, and the corner of the map shows the current weather at the farm: temperature, sky, humidity, wind and chance of rain. At the bottom you always have the coordinates of the point under the cursor (WGS84 and Stereo70), the zoom and the scale.

For each year you see the list of crops, with the number of parcels and the total area (for example: 520 sunflower parcels on 778 ha). You switch each crop on or off separately, compare years and move from measured crops to those declared for subsidies (APIA). A whole year downloads in one click, with one file per crop.

At high zoom you see the exact parcel boundaries, farm tracks, unworked strips and neighbouring fields. Coordinates, zoom and map scale (for example 1:7,400) update as you move, and a click on any parcel opens its complete sheet.

The first page shows the year, the identification zone, the layer (measured or APIA) and the area, in hectares and square metres. The rest of the data — soil, climate, satellite — is fetched by itself in the background as soon as you open the sheet, and the top bar shows what has already loaded. The sheet can be maximised to full screen, while the parcel stays highlighted on the map.

Texture follows the USDA classification (for example clay loam: 40% clay, 38% silt, 22% sand), with its practical meaning: how well it holds water and how easily it compacts. pH is shown on a colour scale, with its implications for nutrients. The chemical and physical composition brings together organic carbon, total nitrogen, cation exchange capacity (CEC), bulk density, gravel and clay. Organic carbon is also shown by depth (0–5, 5–15, 15–30 cm), and at the end you get agronomic recommendations in plain language, derived from the soil profile.

Soil moisture is shown at three depths — the arable layer (0–7 cm), the root zone (7–28 cm) and the deep reserve (28–100 cm) — each with its status: dry, low, optimal or saturated. The temperature chart shows daily minimums and maximums, with the hottest and coldest days marked, and a monthly table sums up averages and extremes. Precipitation is shown day by day, with the total and the number of rainy days. Finally come the agronomic indices calculated from the daily series: growing degree days (GDD), vapour pressure deficit (VPD), water balance (rain minus evapotranspiration), air humidity, frost days and heat-stress days.

You see the season’s mean and peak NDVI, with every pass as a bar (a stronger colour means fewer clouds), plus the health indices NDMI (leaf moisture), EVI (biomass), NDRE (nitrogen) and LAI (leaf area), each with its interpretation — for example “possible N deficit” or “reduced canopy”. You find out which pass was the best and which the cloudiest, and when clouds covered much of the parcel you get a warning about how reliable the data is. Besides the Summary there is an advanced view: timeline, month by month and charts.

For every month the app looks up all the Sentinel-2 scenes covering the parcel and picks the clearest one. The map shows the parcel outlined plus a margin around it (neighbours, roads, villages) for reference; cloud-covered pixels are shown in grey and left out of the calculation. Under each image you get the scene date, the parcel’s NDVI and NDMI, the cloud cover, and the month’s precipitation and temperatures, and above the grid you switch between the satellite photo and the NDVI, NDMI, EVI and NDRE maps. The “AI month analysis” button explains the chosen month — summary, vegetation, water, climate and recommended actions — based on the image, that month’s weather, the soil and the crop. The example in the image, a wheat parcel in 2020, reads like a story: the crop greens up from February (NDVI 0.48), peaks in April–May (0.84), ripens in June (0.65) and is harvested by July (0.30); after the autumn field work in October (0.18), vegetation returns in November–December (0.45–0.50).

The charts show the peak NDVI of each year and the water balance over the April–September season (rain minus evapotranspiration). For every year you get the crop, NDVI, NDMI, water balance, the month of peak vegetation and a short conclusion — for example “good vegetation, despite a water deficit”. If the parcel geometry changed by more than 10% between years, the app warns you that, in that case, the comparison is indicative.

You see the sequence by year (for example maize, maize, sunflower, soybean, wheat), coloured by type: legumes, maize and other crops. Below it there is a summary with the number of years in the history, the number of distinct crops and how many times the same crop was repeated. When the same crop returns too often, a warning appears, so you can keep an eye on the pressure on the soil.

For the chosen year you see the overall verdict (for example “Difficult season, vegetation affected”), the verdict for each source and the recommended actions, then the AI interpretation of the crop season: overall verdict, soil, climate, vegetation and proposed actions. Next come the confidence level per source (soil, climate, satellite, geometry) and the data collected. The report downloads in three versions: a PDF with text, tables and charts, ready to print or email; a geo PDF that adds the parcel map at the best zoom, the centroid in WGS84 and the geographic extent — useful for subsidy files or archives; and GeoJSON with the parcel geometry.

The file has tabs for the document data, property data, persons, rights and encumbrances, notes and geometry. On each one you add records (for example deeds, with their number and issue date), which you can edit or delete at any time. The PDF is added by dragging it into the area on the left, and the parcel geometry can be changed or edited from the file. The data in the file is yours and you upload it; a new parcel can also be added by importing a CGXML file. A parcel you lease out or lease in is identified directly in the CadSense (opens in a new tab) database, by cadastral, CF, IE or topographic number.